Toward improving re-coloring based clustering with graph b-coloring

Authors:
Hiroki Ogino;Tetsuya Yoshida
Affiliations:
Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan
Venue:
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Year:
2010

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Abstract

This paper proposes an approach toward improving re-coloring based clustering with graph b-coloring. Previous b-coloring based clustering algorithm did not consider the quality of clusters. Although a greedy re-coloring algorithm was proposed, it was still restrictive in terms of the explored search space due to its greedy and sequential re-coloring process. We aim at overcoming the limitations by enlarging the search space for re-coloring, while guaranteeing b-coloring properties. A best first re-coloring algorithm is proposed to realize nongreedy search for the admissible colors of vertices. A color exchange algorithm is proposed to remedy the problem in sequential re-coloring. These algorithms are orthogonal with respect to the re-colored vertices and thus can be utilized in conjunction. Preliminary evaluations are conducted over several benchmark datasets, and the results are encouraging.